InputBlackBoxOutput

import os
from tensorflow.python.profiler import profiler_client

tpu_profile_service_address = os.environ['COLAB_TPU_ADDR'].replace('8470', '8466')
print(profiler_client.monitor(tpu_profile_service_address, 100, 2))

InputBlackBoxOutput

import os
import shutil
import requests
import time
import random

# pip install requests-html
from requests_html import HTMLSession 
session = HTMLSession()

InputBlackBoxOutput

// A workaroud to use clear as a command to clear Command Prompt
// Step 1: g++ clear.cpp -o clear.exe
// Step 2: Add clear.exe directory to PATH enviroment variable

#include<cstdlib>

int main() {
    system("cls");
    return 0;
}

InputBlackBoxOutput

import sys
import serial
import serial.tools.list_ports as port_list

def serial_communication():
    ports = list(port_list.comports())
    if ports == []:
        print("No open ports found!")
        sys.exit()

InputBlackBoxOutput

import os, glob, json
import cv2

class BoundingBoxConvertor:
	def __init__(self):
		self.label_map = {
			"0":"class1",
			"1":"class2",
			"2":"class3"
		}

InputBlackBoxOutput

import requests

headers = {
    'User-Agent': "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
    } 

def get_webpage():
    url = "www.google.com" 
    print(url)
    response = requests.request("GET", url, headers=headers)

InputBlackBoxOutput

import cv2
import numpy as np
import time

greenHSVLowerLimit = (24, 76, 0)
greenHSVUpperLimit = (84, 255, 255)

VideoStream = cv2.VideoCapture(0)
time.sleep(2.0)

InputBlackBoxOutput

import cv2
import numpy as np
import matplotlib.pyplot as plt

image = cv2.imread("sample-images/minions.jpg")
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
plt.imshow(image)

pixel_values = image.reshape((-1, 3))
pixel_values = np.float32(pixel_values)

InputBlackBoxOutput

from xml.dom import minidom
import os
import glob

LUT = {"class0": 0, "class1": 1, "class2": 2}

def convert_coordinates(size, box):
    dw = 1.0/size[0]
    dh = 1.0/size[1]
    x = (box[0]+box[1])/2.0

InputBlackBoxOutput

import glob
import json
import cv2

LUT = {"class0": 0, "class1": 1, "class2": 2}

for each_file in glob.glob("data/*.json"):
	with open(each_file) as json_file:
		data = json.load(json_file)[0]